{"nbformat":4,"nbformat_minor":0,"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.1"},"colab":{"name":"0-understanding-cnn-architecture.ipynb","provenance":[],"collapsed_sections":[]}},"cells":[{"cell_type":"code","metadata":{"id":"0qscW3Ppun1-","executionInfo":{"status":"ok","timestamp":1604772607826,"user_tz":420,"elapsed":353,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["from matplotlib import pyplot as plt\n","from tensorflow.keras.models import Sequential\n","from tensorflow.keras import optimizers\n","from tensorflow.keras.layers import Dense, Activation, Flatten, Conv2D, MaxPooling2D, AveragePooling2D, GlobalMaxPooling2D, ZeroPadding2D, Input\n","from tensorflow.keras.models import Model\n","from tensorflow.keras.datasets import cifar10, mnist\n","from tensorflow.keras.preprocessing import image"],"execution_count":16,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"keXWLYv7un2C"},"source":["## 0. Basics\n","- Input of image-format data is usually 4-D array in Tensorflow\n","<br> **(num_instance, width, height, depth)** </br>\n","    - **num_instance:** number of data instances. Usually designated as **None** to accomodate fluctuating data size\n","    - **width:** width of an image\n","    - **height:** height of an image\n","    - **depth:** depth of an image. Color images are usually with depth = 3 (3 channels for RGB). Black/white images are usually with depth = 1 (only one channel)\n","    \n","<img src=\"http://xrds.acm.org/blog/wp-content/uploads/2016/06/Figure1.png\" style=\"width: 400px\"/>"]},{"cell_type":"markdown","metadata":{"id":"vv-UbATxun2D"},"source":["- Loading image\n","    - Tensors that we have seen so far in MNIST and CIFAR-10 datasets are actually images\n","    - 3-dimensional arrays can be shown as images using ```plt.imshow()``` "]},{"cell_type":"code","metadata":{"id":"U4HfWfnVun2D","executionInfo":{"status":"ok","timestamp":1604772646029,"user_tz":420,"elapsed":1084,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"9d2c1f9c-3fcb-42b8-d142-8e50fb784a27","colab":{"base_uri":"https://localhost:8080/"}},"source":["(x_train, y_train), _ = cifar10.load_data()\n","print(x_train[0].shape)"],"execution_count":20,"outputs":[{"output_type":"stream","text":["(32, 32, 3)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"-nFDDKJMun2G","executionInfo":{"status":"ok","timestamp":1604772454543,"user_tz":420,"elapsed":1546,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"9623319b-b929-4c73-ec63-77d164460bab","colab":{"base_uri":"https://localhost:8080/","height":593}},"source":["# showing figures\n","fig = plt.figure(figsize = (10, 10))\n","for i in range(9):\n","  fig.add_subplot(3, 3, i+1)\n","  plt.imshow(x_train[i])\n","\n","plt.show()"],"execution_count":14,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x720 with 9 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"-QEPYGasun2J","executionInfo":{"status":"ok","timestamp":1604772648519,"user_tz":420,"elapsed":789,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"fcf7ac90-594b-4cf3-ec98-54b05244b03c","colab":{"base_uri":"https://localhost:8080/"}},"source":["(x_train, y_train), _ = mnist.load_data()\n","print(x_train[0].shape)   # Images in mnist are 2-D since they don't have color channel"],"execution_count":21,"outputs":[{"output_type":"stream","text":["(28, 28)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"yCsTEA6Eun2M","executionInfo":{"status":"ok","timestamp":1604772650063,"user_tz":420,"elapsed":1269,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"fd35f106-9159-4e98-a8e0-1c438bda486d","colab":{"base_uri":"https://localhost:8080/","height":593}},"source":["# showing figures\n","fig = plt.figure(figsize = (10, 10))\n","for i in range(9):\n","  fig.add_subplot(3, 3, i+1)\n","  plt.imshow(x_train[i])\n","\n","plt.show()"],"execution_count":22,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x720 with 9 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"8iMTqnCeun2P"},"source":["## 1. Padding\n","- Two types of padding options\n","    - **'valid'**: no padding (drop right-most columns & bottom-most rows)\n","    - **'same'**: padding size **p = [k/2]** when kernel size = **k**\n","- Customized paddings can be given with ZeroPadding**n**D layer"]},{"cell_type":"code","metadata":{"id":"-qKeDj9wun2P","executionInfo":{"status":"ok","timestamp":1604772677158,"user_tz":420,"elapsed":383,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["# when padding = 'valid'\n","model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'valid'))"],"execution_count":23,"outputs":[]},{"cell_type":"code","metadata":{"id":"tbU5lMB8un2S","executionInfo":{"status":"ok","timestamp":1604772677812,"user_tz":420,"elapsed":289,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"57dcb25d-fd16-49da-fe1d-6e1d1a3a8d7d","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":24,"outputs":[{"output_type":"stream","text":["(None, 8, 8, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"AqRbX-Yzun2V","executionInfo":{"status":"ok","timestamp":1604772678544,"user_tz":420,"elapsed":393,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["# when padding = 'same'\n","model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))"],"execution_count":25,"outputs":[]},{"cell_type":"code","metadata":{"id":"iMS8o93Kun2X","executionInfo":{"status":"ok","timestamp":1604772678946,"user_tz":420,"elapsed":189,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"45d2a988-5581-4852-e61e-66692d3e3267","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":26,"outputs":[{"output_type":"stream","text":["(None, 10, 10, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"seGVNy51un2Z","executionInfo":{"status":"ok","timestamp":1604772680928,"user_tz":420,"elapsed":358,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["# user-customized padding\n","input_layer = Input(shape = (10, 10, 3))\n","padding_layer = ZeroPadding2D(padding = (1,1))(input_layer)\n","\n","model = Model(inputs = input_layer, outputs = padding_layer)"],"execution_count":27,"outputs":[]},{"cell_type":"code","metadata":{"id":"_RqVO9trun2c","executionInfo":{"status":"ok","timestamp":1604772681604,"user_tz":420,"elapsed":334,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"1442c176-5231-4a66-e9af-7fb16082e8e5","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":28,"outputs":[{"output_type":"stream","text":["(None, 12, 12, 3)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"b1UlTeB4un2f"},"source":["## 2. FIlter/kernels\n","- Number of filters can be designated\n","- Number of filters equals to the **depth of next layer**"]},{"cell_type":"code","metadata":{"id":"kEV3JgKcun2f","executionInfo":{"status":"ok","timestamp":1604772683260,"user_tz":420,"elapsed":401,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["# when filter size = 10\n","model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))"],"execution_count":29,"outputs":[]},{"cell_type":"code","metadata":{"id":"Wcso06xcun2h","executionInfo":{"status":"ok","timestamp":1604772683575,"user_tz":420,"elapsed":356,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"13435f50-7dec-428f-9cc4-894767e62a37","colab":{"base_uri":"https://localhost:8080/"}},"source":["# you could see that the depth of output = 10\n","print(model.output_shape)"],"execution_count":30,"outputs":[{"output_type":"stream","text":["(None, 10, 10, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"S1O2aqSUun2k","executionInfo":{"status":"ok","timestamp":1604772684303,"user_tz":420,"elapsed":484,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["# when filter size = 20\n","model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 20, kernel_size = (3,3), strides = (1,1), padding = 'same'))"],"execution_count":31,"outputs":[]},{"cell_type":"code","metadata":{"id":"9tTWaDLBun2m","executionInfo":{"status":"ok","timestamp":1604772685164,"user_tz":420,"elapsed":398,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"662c2ec5-f2c8-4f16-e5bf-5a259e85face","colab":{"base_uri":"https://localhost:8080/"}},"source":["# you could see that the depth of output = 20\n","print(model.output_shape)"],"execution_count":32,"outputs":[{"output_type":"stream","text":["(None, 10, 10, 20)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"qbUkO3CAun2o"},"source":["## 3. Pooling\n","- Usually, max pooling is applied for rectangular region\n","- pooling size, padding type, and strides can be set similar to convolutional layer"]},{"cell_type":"code","metadata":{"id":"x1lSGo1sun2p","executionInfo":{"status":"ok","timestamp":1604772687489,"user_tz":420,"elapsed":330,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))"],"execution_count":33,"outputs":[]},{"cell_type":"code","metadata":{"id":"l8Hr8R0Qun2r","executionInfo":{"status":"ok","timestamp":1604772687740,"user_tz":420,"elapsed":336,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"ba2f1a3b-cdff-45f7-bfb6-b9451eccf9de","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":34,"outputs":[{"output_type":"stream","text":["(None, 10, 10, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"dHzT4SYpun2u","executionInfo":{"status":"ok","timestamp":1604772688342,"user_tz":420,"elapsed":561,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["# when 'strides' parameter is not defined, strides are equal to 'pool_size'\n","model.add(MaxPooling2D(pool_size = (2,2), padding = 'valid'))"],"execution_count":35,"outputs":[]},{"cell_type":"code","metadata":{"id":"clUXAYBDun2w","executionInfo":{"status":"ok","timestamp":1604772688511,"user_tz":420,"elapsed":189,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"2715bb59-43a7-4423-b2f6-251c21993fb5","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":36,"outputs":[{"output_type":"stream","text":["(None, 5, 5, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"7tfyU8aOun2y","executionInfo":{"status":"ok","timestamp":1604772689309,"user_tz":420,"elapsed":634,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))\n","model.add(MaxPooling2D(pool_size = (2,2), strides = (1,1), padding = 'valid'))"],"execution_count":37,"outputs":[]},{"cell_type":"code","metadata":{"id":"jkU9ZYx7un21","executionInfo":{"status":"ok","timestamp":1604772689309,"user_tz":420,"elapsed":223,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"41452ce4-7e80-46cf-bf14-7dfa971dce31","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":38,"outputs":[{"output_type":"stream","text":["(None, 9, 9, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"D84advyyun25","executionInfo":{"status":"ok","timestamp":1604772690660,"user_tz":420,"elapsed":352,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))\n","model.add(AveragePooling2D(pool_size = (2,2), padding = 'valid'))"],"execution_count":39,"outputs":[]},{"cell_type":"code","metadata":{"id":"HjKdnR-xun27","executionInfo":{"status":"ok","timestamp":1604772691040,"user_tz":420,"elapsed":422,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"4bc83723-e9c6-43f5-aa17-7b305e099dd6","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":40,"outputs":[{"output_type":"stream","text":["(None, 5, 5, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"0XiM-071un2_","executionInfo":{"status":"ok","timestamp":1604772691337,"user_tz":420,"elapsed":351,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["# globalmaxpooling performs maxpooling over whole channel with depth = 1\n","model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))\n","model.add(GlobalMaxPooling2D())"],"execution_count":41,"outputs":[]},{"cell_type":"code","metadata":{"id":"nmKzY3Njun3C","executionInfo":{"status":"ok","timestamp":1604772692089,"user_tz":420,"elapsed":660,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"5d55a5e9-192b-41c8-961a-098a74117a26","colab":{"base_uri":"https://localhost:8080/"}},"source":["# as the number of filters = 10, 10 values are returned as result of globalmaxpooling2D\n","print(model.output_shape)"],"execution_count":42,"outputs":[{"output_type":"stream","text":["(None, 10)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"cjcD0Q3Qun3F"},"source":["## 4. Flattening\n","- To be connected to fully connected layer (dense layer), convolutional/pooling layer should be **\"flattened\"**\n","- Resulting shape = **(Number of instances, width X height X depth)**"]},{"cell_type":"code","metadata":{"id":"li58qP7Jun3F","executionInfo":{"status":"ok","timestamp":1604772694808,"user_tz":420,"elapsed":295,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))"],"execution_count":43,"outputs":[]},{"cell_type":"code","metadata":{"id":"x2mYfDjKun3H","executionInfo":{"status":"ok","timestamp":1604772695252,"user_tz":420,"elapsed":370,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"c7e048a7-337b-40ae-ac43-9540f0948ce9","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":44,"outputs":[{"output_type":"stream","text":["(None, 10, 10, 10)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"EZKOZKSsun3J","executionInfo":{"status":"ok","timestamp":1604772695463,"user_tz":420,"elapsed":232,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["model.add(Flatten())"],"execution_count":45,"outputs":[]},{"cell_type":"code","metadata":{"id":"HHsOJlSxun3K","executionInfo":{"status":"ok","timestamp":1604772695972,"user_tz":420,"elapsed":363,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"bc69f283-a339-47a9-b4eb-7f7b03babf42","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":46,"outputs":[{"output_type":"stream","text":["(None, 1000)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"6Tlr1kZnun3O"},"source":["## 5. Fully Connected (Dense)\n","- After flattening layer, fully connected layer can be added\n","- output shape (number of nodes) should be designated"]},{"cell_type":"code","metadata":{"id":"Wzh1z34tun3O","executionInfo":{"status":"ok","timestamp":1604772697539,"user_tz":420,"elapsed":335,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}}},"source":["model = Sequential()\n","model.add(Conv2D(input_shape = (10, 10, 3), filters = 10, kernel_size = (3,3), strides = (1,1), padding = 'same'))\n","model.add(Flatten())\n","model.add(Dense(50))"],"execution_count":47,"outputs":[]},{"cell_type":"code","metadata":{"id":"_RrKy1-pun3R","executionInfo":{"status":"ok","timestamp":1604772697914,"user_tz":420,"elapsed":217,"user":{"displayName":"Buomsoo Kim","photoUrl":"","userId":"18268696804115368229"}},"outputId":"4e26d930-7b89-49c6-c811-b8b8207d5c4e","colab":{"base_uri":"https://localhost:8080/"}},"source":["print(model.output_shape)"],"execution_count":48,"outputs":[{"output_type":"stream","text":["(None, 50)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"P7JLRN5E6BYU"},"source":[""],"execution_count":null,"outputs":[]}]}